New whole genome de novo assemblies of three divergent strains of rice (O. sativa) documents novel gene space of aus and indica

New whole genome de novo assemblies of three divergent strains of rice (O. sativa) documents novel gene space of aus and indica

Michael C Schatz, Lyza G Maron, Joshua C Stein, Alejandro Hernandez Wences, James Gurtowski, Eric Biggers, Hayan Lee, Melissa Kramer, Eric Antonio, Elena Ghiban, Mark H Wright, Jer-ming Chia, Doreen Ware, Susan R McCouch, William Richard McCombie

The use of high throughput genome-sequencing technologies has uncovered a large extent of structural variation in eukaryotic genomes that makes important contributions to genomic diversity and phenotypic variation. Currently, when the genomes of different strains of a given organism are compared, whole genome resequencing data are aligned to an established reference sequence. However when the reference differs in significant structural ways from the individuals under study, the analysis is often incomplete or inaccurate. Here, we use rice as a model to explore the extent of structural variation among strains adapted to different ecologies and geographies, and show that this variation can be significant, often matching or exceeding the variation present in closely related human populations or other mammals. We demonstrate how improvements in sequencing and assembly technology allow rapid and inexpensive de novo assembly of next generation sequence data into high-quality assemblies that can be directly compared to provide an unbiased assessment. Using this approach, we are able to accurately assess the ?pan-genome? of three divergent rice varieties and document several megabases of each genome absent in the other two. Many of the genome-specific loci are annotated to contain genes, reflecting the potential for new biological properties that would be missed by standard resequencing approaches. We further provide a detailed analysis of several loci associated with agriculturally important traits, illustrating the utility of our approach for biological discovery. All of the data and software are openly available to support further breeding and functional studies of rice and other species.


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